Advances in neurostimulation for movement disorders
Bibliographic record
Abstract
In just 12 years since its introduction, deep brain stimulation (DBS) has become well established as a safe and effective therapy in the treatment of medically refractory movement disorders. Ventralis intermedius (Vim) DBS has virtually replaced thalamotomy in the routine clinical treatment of essential tremor, affording relief to thousands of patients who previously would not have undergone surgery, and there is increasing usage of Vim DBS in other tremors of intention (e.g., multiple sclerosis). Subthalamic nucleus (STN) and globus pallidus internus (GPi) DBS have revolutionized the treatment of advanced stage Parkinson's disease, improving all cardinal disease features and increasing 'on' time without dyskinesias. Finally, DBS of various sub-cortical structures is being developed and tested in other less prevalent movement disorders such as dystonia. Future developments in this rapidly advancing area will no doubt include widening indications for this relatively safe surgical procedure, elucidation of the mechanisms of action of electrical stimulation, and technological advancements improving effectiveness and convenience.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.007 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".